1. Field of the Invention
The invention relates generally to a system for studying the interaction between rainfall and the potential for fluid runoff in a selected geographic region such as a river basin. The invention further relates to a method for obtaining digital data relating to ground cover and soil type classifications in selected geographic regions using remote sensing techniques.
2. Description of the Related Art
The interaction of rainfall and the potential for fluid runoff is an important consideration for the development and management of geographic sites such as river basins and, in particular, in the construction and operation of such structures as dams and hydroelectric plants. The accurate estimation of flooding potential in a basin is necessary for the proper design of plant components such as dams, spillways and reservoirs and for their proper operation in retaining water in designated areas. Further, the extent to which the soil at a geographic site can absorb water and other fluids is an important consideration for such applications as the installation of reservoirs for recreation and drainage fields for waste water treatment systems.
The extent to which hazardous, and sometimes life-threatening, flooding can occur in a river basin, or more simply the degree to which basin soils are infiltrated by a fluid, is generally estimated using mathematical models and various kinds of data obtained from aerial photographs and actual field trips to various basin areas. A commonly used standard for estimating fluid runoff potential is probable maximum flood (PMF) determination in accordance with a methodology established by the United States Soil Conservation Service. This standard is generally used as a guideline for the safe operation of dams by governmental agencies such as the Federal Energy Regulatory Commission (FERC).
PMF calculations require the determination such parameters as the probable maximum precipitation (PMP) that is likely to occur over a basin and the runoff curve number (RCN) for the basin. Generally, the RCN of a drainage basin provides an indication of its runoff potential and is based on the ground cover within the basin and the hydrologic soil group (HSG) classifications for the soils in the basin. Ground cover generally corresponds to the different classes of land use such as forest, fallow land, and residential and/or commercial development which exist in the area under study. HSG classifications for soil are generally based on the extent of infiltration and transmission of water through the soil and transmission of the water. The United States Soil Conservation Service (SCS) developed the HSG classification system to identify a soil sample as belonging to one of four different classes. The classes, as defined by the SCS, include class A (for soils such as sands and gravels which have high water infiltration rates even when thoroughly wetted and high rates of water transmission), classes B and C (for soils such as silts which are characterized by moderate to slow water infiltration rates when thoroughly wetted and moderate to slow water transmission rates), and class D (for soils such as clays which have very slow water infiltration rates when thoroughly wetted and very slow water transmission rates).
PMF values may have in the past been subject to considerable inaccuracy due to the imprecise methodology used for calculating RCN values. In order to calculate RCN values, the number of acres of each ground cover type and each hydrologic soil combination have to be determined. In the past, data relating to ground covers and soil types have been obtained from regional soils association maps and area specific soil series survey maps prepared by the United States Soil Conservation Service, and quadrangle, soils and geology maps such as those developed by the United States Geological Survey. Many of these sources are outdated, reflecting in many instances the status of the geographic area under study decades removed in time from the current study. Further, many of these sources do not account for the high degree of variability that may exist soil types over short distances, as only relatively sparse soil sampling was undertaken for many of the mapping endeavors.
Several additional drawbacks with respect to previous methods for calculating RCN values are attributable to the manner in which the number of acres for each ground cover/soil type combination in the basin is determined. In the past, mylar sheets have been prepared in an effort to graphically indicate ground cover and soils classes for a prescribed geographic area. These sheets are generally overlaid with a geographical view of the basin which is usually obtained by enlarging one or more regional maps. A grid structure is superimposed over the mylar sheets and the regional map, and the grid squares are counted for each ground cover/soil group combination. The accuracy of this method is heavily dependent on the size of the grid squares chosen for the mylar overlays and the accuracy with which they are applied to the superimposed sheets. Further, substantial inaccuracies in the determination of acreage for each ground cover/soil type combination can arise from the manual estimates made by the human analyst when determining the percentage of a grid square occupied by a particular ground cover or soil type.
The scaling and alignment of the overlays and geographic maps can also contribute substantially to the inaccuracy of ground cover/soil type areal determinations. Scaling and alignment are generally performed manually by making approximate enlargements of maps representing adjacent geographic regions and attempting to align one map with respect to another map using landmarks shown on both of the maps. Errors in the original maps become more pronounced when the maps are enlarged. Further, the erroneous positioning of landmarks on the original maps can cause the areas surrounding the landmark coordinates to be erroneously displaced on the combined map, thereby providing inaccurate information about the soils and ground cover in the region of interest.